Swarm Analytics: Designing Information Markers to Characterise Swarm Systems in Shepherding Contexts

TL;DR

This paper introduces a framework for organizing swarm indicators into information markers, enabling comprehensive external analysis of swarm systems, especially heterogeneous and cognitive swarms, to better understand their dynamics and agent influences.

Contribution

It develops a novel ontological framework for swarm indicators, forming the foundation for the emerging field of swarm analytics focused on top-level swarm understanding.

Findings

Framework for organizing swarm indicators into information markers

Supports detection and recognition of swarm dynamics and agent influences

Applicable to heterogeneous and cognitive swarm systems

Abstract

Contemporary swarm indicators are often used in isolation, focused on extracting information at the individual or collective levels. Consequently, these are seldom integrated to infer a top-level operating picture of the swarm, its members, and its overall collective dynamics. The primary contribution of this paper is to organise a suite of indicators about swarms into an ontologically-arranged collection of information markers to characterise the swarm from the perspective of an external observer\textemdash, a recognition agent. Our contribution shows the foundations for a new area of research that we tile swarm analytics, whose primary concern is with the design and organisation of collections of swarm markers to understand, detect, recognise, track, and learn a particular insight about a swarm system. We present our designed framework of information markers that offer a new avenue for swarm research, especially for heterogeneous and cognitive swarms that may require more advanced capabilities to detect agencies and categorise agent influences and responses.